MDRB, MDRB Conference Room (218) View map
Outlook users, please download the .ics file to your computer using the clock button above, then go here for instructions on how to add this event feed to your calendar.

701 E. M.L. King Blvd.

#research
View map

The UTC Graduate School is pleased to announce that Evan Gildernew will present Doctoral research titled, COMPUTATIONAL OPTIMIZATION OF PHASE CHANGE MATERIALS ON ADSORBED CARBON DIOXIDE CAPTURE SYSTEMS on 10/05/2023 at 10:00 AM in MDRB Conference Room. Everyone is invited to attend.

Computational Science

Chair: Dr. Sungwoo Yang

Abstract:
Carbon dioxide (CO2) capture and sequester remains a critical area of research in chemical engineering. Novel sorbent/substrate structuring and novel sorbent compositing are emerging fields of research for advancing the efficiency of adsorbent-based capture technologies and establishing the viability of next-generation absorbent-based capture technologies. This work details the development and validation of a finite element model which solves for the fabrication of novel adsorbent structures composited with phase change materials (PCM) optimized in selected design applications. The design applications include internally coated hollow fibers, externally coated annular finned tube, and a jacketed storage vessel, which are presented in reduced computational form. This study reviews the thermofluidic characteristics of selected adsorbents for pairing with phase change materials to be incorporated into sorbent cycling devices, with a discussion of the state of the industry adsorption capture technologies. Extensive description is given to adsorption system characterization and to the computational fluid dynamics (CFD) model formulation. The study takes into consideration the challenges associated with gas theory in multiphysics and multiscale modeling, particularly as they relate to fluid-structure interactions in micro and nanoporous regions. This research aims to provide a foundation for further advancements in computational methodologies applied to CO2 capture processes which incorporate learning algorithms that provide optimized material and device designs. Model results generate gas capture values and allow for the examination of domain isotherms and kinetics. Utilizing the L-BFGS optimization method, a distribution of phase change material within an activated carbon adsorbent bed was determined to improve CO2 uptake across device designs.

Event Details

  • Kelsey M Saylor

1 person is interested in this event

User Activity

No recent activity